Literature DB >> 16876364

Microarray analysis of variation in individual aging C. elegans: approaches and challenges.

T R Golden1, A Hubbard, S Melov.   

Abstract

Aging is generally defined and studied as a population phenomenon. However, there is great interest, especially when discussing human aging, in the identification of factors that influence the life span of an individual organism. The nematode Caenorhabditis elegans provides an excellent model system for the study of aging at the level of the individual, since young nematodes are essentially clonal yet experience a large range of individual life spans. We are conducting gene expression profiling of individual nematodes, with the aim of discovering genes that vary stochastically in expression between individuals of the same age. Such genes are candidates to modulate the ultimate life span achieved by each individual. We here present statistical analysis of gene expression profiles of individual nematodes from two different microarray platforms, examining the issue of technical vs. biological variance as it pertains to uncovering genes of interest in this paradigm of individual aging.

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Year:  2006        PMID: 16876364     DOI: 10.1016/j.exger.2006.06.034

Source DB:  PubMed          Journal:  Exp Gerontol        ISSN: 0531-5565            Impact factor:   4.032


  10 in total

1.  Flies selected for longevity retain a young gene expression profile.

Authors:  Pernille Sarup; Peter Sørensen; Volker Loeschcke
Journal:  Age (Dordr)       Date:  2010-07-07

Review 2.  Systems biology of aging in four species.

Authors:  Jacob M Zahn; Stuart K Kim
Journal:  Curr Opin Biotechnol       Date:  2007-08-02       Impact factor: 9.740

3.  Antioxidant properties of blirubin in the model organism, Caenorhabditis elegans.

Authors:  Danny McCaughan; Catherine Au; Alexandre Benedetto; Dejan Milatovic; Judy Aschner; Michael Aschner
Journal:  Int J Neuroprot Neuroregener       Date:  2008

Review 4.  Developmental biomarkers of aging in Caenorhabditis elegans.

Authors:  Zachary Pincus; Frank J Slack
Journal:  Dev Dyn       Date:  2010-05       Impact factor: 3.780

5.  Genome-wide patterns of gene expression during aging in the African malaria vector Anopheles gambiae.

Authors:  Mei-Hui Wang; Osvaldo Marinotti; Anthony A James; Edward Walker; John Githure; Guiyun Yan
Journal:  PLoS One       Date:  2010-10-13       Impact factor: 3.240

Review 6.  Caenorhabditis elegans 2007: the premier model for the study of aging.

Authors:  Thomas E Johnson
Journal:  Exp Gerontol       Date:  2007-10-01       Impact factor: 4.032

7.  Quantitative measurement of aging using image texture entropy.

Authors:  Lior Shamir; Catherine A Wolkow; Ilya G Goldberg
Journal:  Bioinformatics       Date:  2009-10-06       Impact factor: 6.937

8.  Genome-scale studies of aging: challenges and opportunities.

Authors:  Mark A McCormick; Brian K Kennedy
Journal:  Curr Genomics       Date:  2012-11       Impact factor: 2.236

9.  Analysis of nonlinear gene expression progression reveals extensive pathway and age-specific transitions in aging human brains.

Authors:  Kajia Cao; Paul Ryvkin; Yih-Chii Hwang; F Brad Johnson; Li-San Wang
Journal:  PLoS One       Date:  2013-10-03       Impact factor: 3.240

Review 10.  Proteostasis and longevity: when does aging really begin?

Authors:  John Labbadia; Richard I Morimoto
Journal:  F1000Prime Rep       Date:  2014-02-03
  10 in total

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